Dissertação

Produção e caracterização de carvões ativados de caroços de açaí e sua aplicação no tratamento de água de manancial superficial

This study aimed to produce activated Carbon from açai seeds, using NaOH and ZnCl2 for activating agent, to determine some physic-chemical properties of the AC and evaluated the use of AC from acai lumps as filter material in four filters to evaluate the quality of water from the surface spring. Fou...

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Autor principal: SOUSA, Mônica Silva de
Grau: Dissertação
Idioma: por
Publicado em: Universidade Federal do Pará 2019
Assuntos:
Acesso em linha: http://repositorio.ufpa.br/jspui/handle/2011/12018
Resumo:
This study aimed to produce activated Carbon from açai seeds, using NaOH and ZnCl2 for activating agent, to determine some physic-chemical properties of the AC and evaluated the use of AC from acai lumps as filter material in four filters to evaluate the quality of water from the surface spring. Four filters containing the support layer and the filter layer were added, two of them being CA-ZnCl2 with a particle size of 2.4 mm to 4.8 mm (Filter 1) and a particle size of 1.2 mm to 2.0 mm (Filter 2). The other 2 filters had a CA-NaOH filtering layer of the same granulometry, 1.2 mm to 2.0 mm (Filter 3) and 2.4 mm to 4.8 mm (Filter 4). The Filters were installed and monitored at the Multi-user Water Treatment Laboratory (LAMAG) of the Federal University of Pará (UFPA). The physical-chemical variables evaluated in the CAs were: moisture content, volatile material content, ash content, fixed carbon content, pH, SEM and adsorption test with methylene blue. In the physical characterization the results between the two types of coals were similar, in the adsorption tests of AM the granulometry of 1.2 mm obtained better adsorption efficiency presenting 70% of adsorption efficiency for the CA-Zncl2 and 90% for the CA -NaOH. The water quality variables evaluated in the filter monitoring were apparent color, turbidity, pH, total alkalinity and electrical conductivity. Filters 1 and 2 obtained the best results, mainly in the removal of color and turbidity; they were able to remove 43.6% and 39% of apparent color and more than 50% of water turbidity, comparing with surface water data before passing through filtration. Through the analysis of main components, it was possible to observe 3 components that together explained more than 80% of the variance. The variables apparent color and turbidity in filters 1 and 2 correlated positively, indicating improvement in filtered water quality. While the correlation between apparent color and conductivity in filters 3 and 4 corresponds to the worsening of the results of these variables.